Most providers of digital maps rely on a very detailed topographical map database which stores the underlying data. For example, Ordnance Survey uses a very large scale topographic product OS MasterMap™, which records every feature larger than a few metres in one continuous dataset, and is constantly being updated. The OS MasterMap™ product is composed of discrete vector features, each of which has the feature type, geometry, and various feature attributes. The OS MasterMap™ product is recognised as being one of the most accurate and nationally consistent set of these discrete vector features.
To improve the accuracy of third party map data or other new map products, or conversely to improve the topographical data of the map provider itself, it is desirable to compare and combine the topographical data stored in a geographic information system (GIS) with third party map data, which may be less or more spatially accurate. Such third party data may also include map data relating to features not already stored in the GIS, or it may be missing map data relating to features that are stored in the GIS. For example, where the topographic features represent rail lines, map data from the organisation that built the rail network may be more accurate and up to date than that stored in the map provider's database (or vice versa).
One reason for doing this is that the accuracy of the apparent location of a feature as recorded in the topographical map database or the third party data is dependent on a number of different factors that can lead to inconsistencies in the map data. For example, errors in the map data may be due to undefined feature boundaries caused by the surrounding terrain, for example, trees covering paths, or by errors in the measuring instruments used to generate the map data. It is also common for errors to occur where there are multiple features within an area that are spatially very similar, for example, a road network, to the extent that the visual resolution of the measuring instruments is not high enough to distinguish between the those features, This is particularly the case for line features such as paths, tracks, cycle routes, rail lines, highways and the like, as such features tend to be of extreme length which are often difficult and impractical to field check. Furthermore, for features such as railways and highways that are often subject to frequent change, it is not uncommon for the topographical data stored in the GIS system to be incorrect. Therefore, it is desirable for the GIS system creating the map to compare third party attribution to the stored data and, where appropriate, spatially resolve the two map datasets to obtain a more accurate and up to date representation of those features. Similarly, it may be the topographical data stored in the GIS system of the map provider that is the most accurate and up to date, in which case a third party may wish to use the topographical map data stored in the GIS system to improve their own map data.
Previous methods of spatially matching topographical map data include a standard intersection method, wherein features produce a match result if they are found to intersect at any point. Such a method is shown in FIG. 1, wherein a reference feature 10 is compared with three test features 12, 14, and 16. The outcome of this intersection query, as shown by FIG. 1b, is a match against test feature 16 as this is the only test feature that intersects with the reference feature 10. This result is not a good match as it clearly does not relate to the same vector feature. Therefore, this intersection method does not provide a reliable method of matching multiple data sets. This is a particular problem for topographical map data where it is common for features to be overlapping, for example, in a rail or highway network.
Another method of spatially matching topographical map features, which aimed to address the problems of the above described method, is that proposed in “A simple positional accuracy measure for linear features”, M F Goodchild and G J Hunter, Int. J. Geographical Information Science, 1997, volume 11, no. 3, pages 299-306. With reference to FIG. 2a, this paper proposed a method wherein a buffer 24 of width x was placed around a reference source feature 20, the proportion of a test feature 22 lying within that buffer 24 being calculated as a percentage. The problem with this method, as will be described in more detail below, is that if there is more than one test feature and those test features are very similar (i.e. a similar proportion of the feature lies within the buffer), it is still hard to decipher which of those test features is the more accurate spatial match. Again, this is particularly problematic for areas of maps that are largely populated by spatially similar topographical map features such as rail and highway networks.
Therefore, an approach to spatial matching which can provide a more precise measure of the accuracy of topological map features is required to thereby enable multiple maps to be spatially resolved and combined.